Analyzing textual data is a very challenging task because of the huge volume of data generated daily. Fundamental issues in text analysis include the lack of structure in document datasets, the need for various preprocessing steps and performance and scaling issues. Existing text analysis architectures partly solve these issues, providing restrictive data schemas, addressing only one aspect of ...

The main research question addressed in this two-phase descriptive study was 'What are the values underlying nurses' professional identity as expressed through what is meaningful in nurses' work? The first phase was a survey of 767 randomly selected nurses with one, five, and 10 years of experience in nursing, and in the second phase data on work-meaning were obtained from a convenience sample ...

this study is an attempt at examining staged photography series “by an eye witness” by azadeh akhlaghi. in these photos, historical events were reconstructed by staged photography and a reflection of the photographer's attitude towards the moments of death, murder, and burial of the people who made turning points in the contemporary history of iran could be observed. in this series two typ...

In this article, I outline hermeneutic single-case efficacy design (HSCED), an interpretive approach to evaluating treatment causality in single therapy cases. This approach uses a mixture of quantitative and qualitative methods to create a network of evidence that first identifies direct demonstrations of causal links between therapy process and outcome and then evaluates plausible nontherapy ...

Data-Oriented Translation (DOT), which is based on Data-Oriented Parsing (DOP), comprises an experience-based approach to translation, where new translations are derived with reference to grammatical analyses of previous translations. Previous DOT experiments [Poutsma, 1998, Poutsma, 2000a, Poutsma, 2000b] were small in scale because important advances in DOP technology were not incorporated in...

Abstract Although existing super-resolution networks based on deep learning have obtained good results, it is still challenging to achieve an ideal visual effect for irregular texts, especially spatially deformed ones. In this paper, we propose a robust Bezier Curve-based image network (BCSR), which can efficiently handle the degradation caused by deformations. Firstly, arbitrarily shaped text ...